Merge pull request #4287 from lamblin/fix_neg_bool

theano/scalar/basic.py

@@ -2399,9 +2399,19 @@ round_half_away_from_zero = RoundHalfAwayFromZero(same_out_float_only)
 
 
 class Neg(UnaryScalarOp):
+    # We can use numpy.negative here, because even if it gives unexpected
+    # results on Boolean arrays, it will be passed other dtypes as Theano
+    # does not have a Boolean type for tensors.
     nfunc_spec = ('negative', 1, 1)
 
     def impl(self, x):
+        # We have to make sure x is not a numpy.bool_, because
+        # `-numpy.bool_(True)` is `False` (we want 0), and
+        # `-numpy.bool_(False)` is `True` (we want 1).
+        # This happens for Composite, as the intermediate results are not
+        # casted in the dtype of the intermediate variable in general.
+        if isinstance(x, numpy.bool_):
+            x = numpy.int8(x)
         return -x
 
     def grad(self, inputs, gout):

theano/scalar/tests/test_basic.py

@@ -155,6 +155,17 @@ class test_composite(unittest.TestCase):
         si3 = theano.scalar.float32()
         sop.make_node(si0 * si3, si1, si2)
 
+    def test_composite_neg_bool(self):
+        # Check that taking the negation of a Boolean intermediate value
+        # works correctly with Python code. It used to be an issue because
+        # `-numpy.bool_(True)` is False and `-numpy.bool_(False)` is True.
+        x = floats('x')
+        y = - (x > 0)
+        z = Composite([x], [y]).make_node(x).outputs[0]
+        f = theano.function([x], z, mode=theano.Mode(linker='py'))
+        for inp, out in zip([-1, 0, 1], [0, 0, -1]):
+            self.assertTrue(f(inp) == out)
+
 
 class test_logical(unittest.TestCase):
     def test_gt(self):

theano/tensor/tests/test_basic.py

@@ -8105,6 +8105,15 @@ def test_symbolic_slice():
     output = a.eval({x: numpy.zeros((5, 4, 3, 2), dtype=theano.config.floatX)})
     assert output == numpy.array(5)
 
+
+def test_composite_neg_bool():
+    # Check that taking the negation of a Boolean intermediate value
+    # works correctly with Python code. It used to be an issue because
+    # `-numpy.bool_(True)` is False and `-numpy.bool_(False)` is True.
+    x = theano.tensor.vector()
+    f = theano.function([x], - (x > 0), mode=theano.Mode(linker='py'))
+    utt.assert_allclose(f([-1, 0, 1]), [0, 0, -1])
+
 """
 
 if __name__ == '__main__':